Journal ArticleDOI
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Petre Stoica,Prabhu Babu,Jian Li +2 more
TLDR
This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing, obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many- snapshot cases but can be used even in single-snapshot situations.Abstract:
This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing. The proposed approach is obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many-snapshot cases but can be used even in single-snapshot situations. SPICE has several unique features not shared by other sparse estimation methods: it has a simple and sound statistical foundation, it takes account of the noise in the data in a natural manner, it does not require the user to make any difficult selection of hyperparameters, and yet it has global convergence properties.read more
Citations
More filters
Journal ArticleDOI
Direction-Of-Arrival Estimation Using AMLSS Method
TL;DR: In this paper, the AMLSS method was proposed for DOA estimation of narrow-band signals, where the distribution of covariance matrix estimation error was used for Maximum Likelihood estimation of potential source signals variances.
Journal ArticleDOI
Bias and Variance in Frequency Estimation at the Leading Edge of a Peak in the Spectrum of a Windowed Signal Under Multipath Mitigation
TL;DR: Since the edge estimation procedure increases the variance of the estimated frequency, this paper presents an analytical method for assessing this increase and describes a method that combines the advantages of peak and edge estimation.
Journal ArticleDOI
Online Sparse DOA Estimation Based on Sub-Aperture Recursive LASSO for TDM-MIMO Radar
Jiawei Luo,Yongwei Zhang,Jian Yang,Donghui Zhang,Yongchao Zhang,Yin Zhang,Yulin Huang,Andreas Jakobsson +7 more
TL;DR: This paper proposes an online LASSO method for efficient direction–of–arrival (DOA) estimation of the TDM–MIMO radar based on the receiving features of the sub–aperture data blocks, which allows for much less iterations, avoiding high–dimensional matrix operations, and the computational complexity is reduced from OK3 to OK2.
Proceedings Article
Sparse spectral-line estimation for nonuniformly sampled multivariate time series: SPICE, LIKES and MSBL
Prabhu Babu,Petre Stoica +1 more
TL;DR: This paper numerically compares the performance of SPICE and LIKES with that of the recently introduced method of multivariate sparse Bayesian learning (MSBL).
Journal ArticleDOI
Sparse covariance fitting for direction of arrival estimation
Luis Blanco,Montse Najar +1 more
TL;DR: A new algorithm for finding the angles of arrival of multiple uncorrelated sources impinging on a uniform linear array of sensors based on sparse signal representation that is able to provide high resolution with a low computational burden.
References
More filters
Journal ArticleDOI
Regression Shrinkage and Selection via the Lasso
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Journal ArticleDOI
Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones
TL;DR: This paper describes how to work with SeDuMi, an add-on for MATLAB, which lets you solve optimization problems with linear, quadratic and semidefiniteness constraints by exploiting sparsity.
Book
Interior-Point Polynomial Algorithms in Convex Programming
TL;DR: This book describes the first unified theory of polynomial-time interior-point methods, and describes several of the new algorithms described, e.g., the projective method, which have been implemented, tested on "real world" problems, and found to be extremely efficient in practice.
Book
Spectral analysis of signals
Petre Stoica,Randolph L. Moses +1 more
TL;DR: 1. Basic Concepts. 2. Nonparametric Methods. 3. Parametric Methods for Rational Spectra.
Related Papers (5)
Two decades of array signal processing research: the parametric approach
Hamid Krim,Mats Viberg +1 more